Impact of ocean data assimilation on climate predictions with ICON-ESM.
We develop a data assimilation scheme with the Icosahedral Non-hydrostatic Earth System Model (ICON-ESM) for operational decadal and seasonal climate predictions at the German weather service. For this purpose, we implement an Ensemble Kalman Filter to the ocean component as a first step towards a w...
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Online Access: | http://hdl.handle.net/21.11116/0000-000B-37F1-7 http://hdl.handle.net/21.11116/0000-000D-588A-5 |
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ftpubman:oai:pure.mpg.de:item_3432080 2023-08-27T04:08:08+02:00 Impact of ocean data assimilation on climate predictions with ICON-ESM. Pohlmann, H. Brune, S. Fröhlich, K. Jungclaus, J. Sgoff, C. Baehr, J. 2023-06 application/pdf http://hdl.handle.net/21.11116/0000-000B-37F1-7 http://hdl.handle.net/21.11116/0000-000D-588A-5 eng eng info:eu-repo/semantics/altIdentifier/doi/10.1007/s00382-022-06558-w http://hdl.handle.net/21.11116/0000-000B-37F1-7 http://hdl.handle.net/21.11116/0000-000D-588A-5 info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/4.0/ Climate Dynamics info:eu-repo/semantics/article 2023 ftpubman https://doi.org/10.1007/s00382-022-06558-w 2023-08-02T01:58:17Z We develop a data assimilation scheme with the Icosahedral Non-hydrostatic Earth System Model (ICON-ESM) for operational decadal and seasonal climate predictions at the German weather service. For this purpose, we implement an Ensemble Kalman Filter to the ocean component as a first step towards a weakly coupled data assimilation. We performed an assimilation experiment over the period 1960-2014. This ocean-only assimilation experiment serves to initialize 10-year long retrospective predictions (hindcasts) started each year on 1 November. On multi-annual time scales, we find predictability of sea surface temperature and salinity as well as oceanic heat and salt contents especially in the North Atlantic. The mean Atlantic Meridional Overturning Circulation is realistic and the variability is stable during the assimilation. On seasonal time scales, we find high predictive skill in the tropics with highest values in variables related to the El Niamp;amp;ntilde;o/Southern Oscillation phenomenon. In the Arctic, the hindcasts correctly represent the decreasing sea ice trend in winter and, to a lesser degree, also in summer, although sea ice concentration is generally much too low in both hemispheres in summer. However, compared to other prediction systems, prediction skill is relatively low in regions apart from the tropical Pacific due to the missing atmospheric assimilation. In addition, we expect a better fine-tuning of the sea ice and the oceanic circulation in the Southern Ocean in ICON-ESM to improve the predictive skill. In general, we demonstrate that our data assimilation method is successfully initializing the oceanic component of the climate system. Article in Journal/Newspaper Arctic North Atlantic Sea ice Southern Ocean Max Planck Society: MPG.PuRe Arctic Pacific Southern Ocean Climate Dynamics |
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Open Polar |
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Max Planck Society: MPG.PuRe |
op_collection_id |
ftpubman |
language |
English |
description |
We develop a data assimilation scheme with the Icosahedral Non-hydrostatic Earth System Model (ICON-ESM) for operational decadal and seasonal climate predictions at the German weather service. For this purpose, we implement an Ensemble Kalman Filter to the ocean component as a first step towards a weakly coupled data assimilation. We performed an assimilation experiment over the period 1960-2014. This ocean-only assimilation experiment serves to initialize 10-year long retrospective predictions (hindcasts) started each year on 1 November. On multi-annual time scales, we find predictability of sea surface temperature and salinity as well as oceanic heat and salt contents especially in the North Atlantic. The mean Atlantic Meridional Overturning Circulation is realistic and the variability is stable during the assimilation. On seasonal time scales, we find high predictive skill in the tropics with highest values in variables related to the El Niamp;amp;ntilde;o/Southern Oscillation phenomenon. In the Arctic, the hindcasts correctly represent the decreasing sea ice trend in winter and, to a lesser degree, also in summer, although sea ice concentration is generally much too low in both hemispheres in summer. However, compared to other prediction systems, prediction skill is relatively low in regions apart from the tropical Pacific due to the missing atmospheric assimilation. In addition, we expect a better fine-tuning of the sea ice and the oceanic circulation in the Southern Ocean in ICON-ESM to improve the predictive skill. In general, we demonstrate that our data assimilation method is successfully initializing the oceanic component of the climate system. |
format |
Article in Journal/Newspaper |
author |
Pohlmann, H. Brune, S. Fröhlich, K. Jungclaus, J. Sgoff, C. Baehr, J. |
spellingShingle |
Pohlmann, H. Brune, S. Fröhlich, K. Jungclaus, J. Sgoff, C. Baehr, J. Impact of ocean data assimilation on climate predictions with ICON-ESM. |
author_facet |
Pohlmann, H. Brune, S. Fröhlich, K. Jungclaus, J. Sgoff, C. Baehr, J. |
author_sort |
Pohlmann, H. |
title |
Impact of ocean data assimilation on climate predictions with ICON-ESM. |
title_short |
Impact of ocean data assimilation on climate predictions with ICON-ESM. |
title_full |
Impact of ocean data assimilation on climate predictions with ICON-ESM. |
title_fullStr |
Impact of ocean data assimilation on climate predictions with ICON-ESM. |
title_full_unstemmed |
Impact of ocean data assimilation on climate predictions with ICON-ESM. |
title_sort |
impact of ocean data assimilation on climate predictions with icon-esm. |
publishDate |
2023 |
url |
http://hdl.handle.net/21.11116/0000-000B-37F1-7 http://hdl.handle.net/21.11116/0000-000D-588A-5 |
geographic |
Arctic Pacific Southern Ocean |
geographic_facet |
Arctic Pacific Southern Ocean |
genre |
Arctic North Atlantic Sea ice Southern Ocean |
genre_facet |
Arctic North Atlantic Sea ice Southern Ocean |
op_source |
Climate Dynamics |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.1007/s00382-022-06558-w http://hdl.handle.net/21.11116/0000-000B-37F1-7 http://hdl.handle.net/21.11116/0000-000D-588A-5 |
op_rights |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.1007/s00382-022-06558-w |
container_title |
Climate Dynamics |
_version_ |
1775348834269921280 |